Artificial Intelligence - M0K05 - Studies portal

The master's degree in Artificial Intelligence aim is to train highly qualified professionals who have the knowledge and values required to solve complex problems, hold positions of responsibility in companies, and carry out theoretical and practical research in artificial intelligence.

This interuniversity master's degree provides a comprehensive, innovative perspective of this field and its application to real situations. The contents are focused on knowledge, representation and reasoning, automatic learning, natural language processing, autonomous agents, robotics and artificial vision and visualization. It focuses on functional techniques to design and construct intelligent systems, so that graduates of this course can apply their skills in a wide range of areas.

The master's degree in Artificial Intelligence (AI) is aimed at people with qualifications in engineering (computer, electronics, etc.), cognitive sciences, mathematics, physics, linguistics or philosophy.

Basic information

Type	Master's degree
Faculty or school	Faculty of Mathematics and Computer Science
Branch of knowledge	Computer and systems engineering
Mode of delivery	Presencial
Credits	90
Number of places available	50
Length of course	2 academic years
Language(s) of instruction	English
Coordination	MAITE LOPEZ SANCHEZ
Course details	Indicators
Lead to doctoral studies	Yes
Admission for applicants not holding a degree qualification	No
Main university information	Master's degree course homepage
Interuniversity	Yes
Main university	Universitat Politècnica de Catalunya
Universities	Universitat Politècnica de Catalunya Universitat Barcelona Universitat Rovira i Virgili
Bridging courses	No

Objectives and competences

Objectives

Competences

Access and admission

Applicant profile and access requirements

Recommended applicant profile

Access requirements and conditions

Pre-enrolment

Calendar

La preinscripció es realitza a la universitat coordinadora del màster.

Més informació

Required documentation

Selection criteria

Notification

Enrolment

As a general rule, at the UB you will be required to enrol online. Remember that you can lose your place if you do not enrol on the day you have been assigned

Welcome

Course curriculum

Subjects and course plans

Distribution of credits

Type	ECTS
Compulsory	33
Optional	39
Compulsory placements	0
Compulsory final project	18
TOTAL	90

List of subjects

Subject	Type	Credits
Specialization: Artificial Intelligence
Advanced Human Language Technologies	Optional	5
Advanced Machine Learning Techniques	Optional	5
Advanced Natural Language Processing	Optional	5
Advanced Topics in Computational Intelligence	Optional	4
Artificial Intelligence in Health Care	Optional	3
Artificial Intelligence Seminar	Optional	3
Artificial Vision and Pattern Recognition	Compulsory	4.5
Assistive and Health-Care Technologies	Optional	4.5
Big Data Analytics	Optional	4.5
Cognitive Interaction with Robots	Optional	4.5
Cognitive Robotics	Optional	4.5
Complex Networks	Optional	5
Computational Vision	Compulsory	5
Constraint Processing and Programming	Optional	4.5
Deep Learning for Medical Image Analysis	Optional	3
Deep Learning	Optional	4.5
Final Project	Compulsory	18
Human Language Engineering	Optional	4.5
Human-Computer Interfaces	Optional	4.5
Intelligent Data Analysis and Data Mining	Optional	4.5
Intelligent Data Analysis Applications in Business	Optional	2
Intelligent Decision Support Systems	Optional	4.5
Intelligent System Project	Optional	3
Introduction to Human Language Technology	Compulsory	5
Introduction to Machine Learning	Compulsory	5
Introduction to Multi-Agent Systems	Compulsory	5
Knowledge Representation and Engineering	Optional	6
Logic and Artificial Intelligence	Optional	6
Machine Learning in Computer Graphics	Optional	3
Minds, Brains and Machines	Optional	4
Multi Agent Systems Design	Optional	4
Multi-Agent Systems	Optional	4
Multi-Criteria Decision Support Systems	Optional	4.5
Multi-Robot Systems	Optional	4.5
New Trends in Robotics	Optional	3
Normative and Dynamic Virtual Worlds	Optional	4.5
Object Recognition	Optional	4
Personalized Multicriteria Decision-Support Systems	Optional	4.5
Planning and Approximate Reasoning	Optional	5
Probabilistic Graphical Models	Optional	4.5
Professional Practice in Artificial Intelligence	Optional	3
Self-Organizing Agent Systems	Optional	4.5
Supervised and Experimental Learning	Optional	4.5
Unsupervised and Reinforcement Learning	Optional	4.5

Previous years

Teaching staff

List of spring and autumn teaching staff on a current course

Placements

Placements in a company or another type of organization are an integral part of university studies, providing first-hand experience of working methodologies in students' chosen professional fields. They offer invaluable practical experience for the transition into work after graduation.

Placements are supervised by tutors and subject to assessment. They are therefore included in the academic record. There is also an option to complete non-curricular placements of up to 500 hours, which can be extended to 900 hours. For both curricular and non-curricular placements, an educational cooperation agreement is signed between the UB and the company, institution or other organization at which the placement will be carried out.

Institutional information